文献类型：期刊文献

英文题名：Two Types of Stability Criteria for Incommensurate Fractional-Order Inertial Delay BAM Neural Networks

作者：Xu, Danning[1];Wei, Liu[1]

机构：[1]Shaoxing Univ, Publ Fundamental Educ Sch, Yuanpei Coll, Shaoxing 312000, Peoples R China

年份：2025

卷号：57

期号：3

外文期刊名：NEURAL PROCESSING LETTERS

收录：SCI-EXPANDED(收录号：WOS:001503370600001)、、EI(收录号：20252318566217)、Scopus(收录号：2-s2.0-105007458983)、WOS

基金：Science Project of Zhejiang Educational Department (No.Y202454310); Science Project of Shaoxing University (No. 2022LG1017); Science Project of Shaoxing University Yuanpei College (KY2023C01).

语种：英文

外文关键词：Incommensurate fractional-order derivative; Inertial delay; BAM neural network; Global Mittag-Leffler stability; Finite time stability

外文摘要：This study explores the global Mittag-Leffler stability and finite time stability of incommensurate fractional-order inertial delay BAM neural networks. Initially, the system, characterized by high-order incommensurate fractional-order dynamics, is transformed into a low-order system through an appropriate variable substitution. Subsequently, sufficient conditions for the achievement of global Mittag-Leffler stability and finite time stability are derived. These conditions are based on the properties of the Riemann-Liouville fractional derivative and integral, and the relation of fractional integral inequalities to the Bellman-Gronwall inequality. The efficacy and accuracy of the proposed theoretical results are substantiated through two numerical simulations.